• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1996년도 춘계학술대회 논문집
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• pp.183-187
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• 1996

On the machine measuring system composed of touch trigger probes, a DNC module, a CMM module, an analysis module and a man-machine interface unit was developed. Measuring accuracy is affected by working accuracy of the on the machine measuring system. The working accuracy of the system is due to geometric errors of th machine tool, servo errors of feed drives and positioning errors of probes. In order to compensate for the measuring errors due to the working accuracy, a calibration module was developed. The measuring automation system was realized with the on the machine measuring system and an IBM-PC on the machine center through a RS-232C. It turns the machining machine (CMM). The system is used for dimensional checking of machined components. initial job setup, part identification, identification of machining errors due to deflection and wear of tools. cutter run out, and calibration of machine tools. A horizontal machining center equipped with FANUC OMC wre used for verification of the system. The validity and reliability of the system. The validity and reliability of the system were confirmed through a series of experiments with gage blocks, ring gages, comparison measurement with a commercial CMM, and so on.

• International Journal of Precision Engineering and Manufacturing
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• 제1권1호
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• pp.111-117
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• 2000

One of the major limitations of productivity and quality in metal cutting is the machining accuracy of machine tools. The machining accuracy is affected by geometric errors, thermally-induced errors, and the deterioration of the machine tools. Geometric and thermal errors of machine tools should be measured and compensated to manufacture high quality products. In metal cutting, the machining accuracy is more affected by thermal errors than by geometric errors. This paper models the thermal errors for error analysis and develops an on-the-machine measurement system by which the volumetric errors are measured and compensated. The thermal error is modeled by means of angularity errors of a column and thermal drift error of the spindle unit which are measured by the touch probe unit with a star type styluses and a designed spherical ball artifact (SBA). Experiments show that the developed system provides a high measuring accuracy, with repeatability of $\pm$2$\mu\textrm{m}$ in X, Y and Z directions. It is believed that the developed measurement system can be also applied to the machine tools with CNC controller. In addition, machining accuracy and product quality can be also improved by using the developed measurement system when the spherical ball artifact is mounted on a modular fixture.

• 한국정밀공학회지
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• 제18권3호
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• pp.61-67
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• 2001

The finishing process for die is an important process because it has influence on final quality of products. Recently s study on development of 5-axis die automated finishing machine has been progressed. But die must be moved from the cutting machine to the die automated finishing machine. So manufacturing cost and time increase and machining error occurs by transfer. So, in this study, a 3-axis machining center was applied to die finishing. Because cutting tool can be changed to finishing tool by ATC, both of cutting and finishing process are possible on the machine. However, this application results in the decrease of finishing for the improvement of form accuracy. So this study focused on the generation of finishing tool path suitable to 3-axis die finishing for the improvement of form accuracy. The form accuracy evaluation is performed by the measurement of removal depth using a stylus profilometer. From the result, it is confirmed that form accuracy was improved less than 2$\mu$m of removal depth error.

• 한국정밀공학회지
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• 제17권1호
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• pp.120-128
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• 2000

One of the major limitations of productivity and quality in metal cutting is the machining accuracy of machine tools. The machining accuracy is affected by geometric errors, thermally-induced errors, and the deterioration of the machine tools. Geometric and thermal errors of machine tools should be measured and compensated to manufacture high quality products. In metal cutting, the machining accuracy is more affected by thermal errors than by geometric errors. This paper models of the thermal errors for error analysis and develops on-the-machine measurement system by which the volumetric error are measured and compensated. The thermal error is modeled by means of angularity errors of a column and thermal drift error of the spindle unit which are measured by the touch probe unit with a star type styluses and a designed spherical ball artifact (SBA). Experiments, performed with the developed measurement system, show that the system provides a high measuring accuracy, with repeatability of $\pm$2${\mu}{\textrm}{m}$ in X, Y and Z directions. It is believed that the developed measurement system can be also applied to the machine tools with CNC controller. In addition, machining accuracy and product quality can be improved by using the developed measurement system when the spherical ball artifact is mounted on the modular fixture.

• 대한방사선기술학회지:방사선기술과학
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• 제42권1호
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• pp.9-17
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• 2019

Although digital mammography is a representative method for breast cancer detection. It has a limitation in detecting and classifying breast tumor due to superimposed structures. Machine learning, which is a part of artificial intelligence fields, is a method for analysing a large amount of data using complex algorithms, recognizing patterns and making prediction. In this study, we proposed a technique to improve the diagnostic accuracy of energy-selective mammography by training data using the machine learning algorithm and using dual-energy measurements. A dual-energy images obtained from a photon-counting detector were used for the input data of machine learning algorithms, and we analyzed the accuracy of predicted tumor thickness for verifying the machine learning algorithms. The results showed that the classification accuracy of tumor thickness was above 95% and was improved with an increase of imput data. Therefore, we expect that the diagnostic accuracy of energy-selective mammography can be improved by using machine learning.

• 한국정밀공학회지
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• 제12권2호
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• pp.37-47
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• 1995

In recent years, it has been variously developed for testing the accuracy of circular motion of NC machine tools, for example Telescoping Ball Bar Method by Bryan, Circular test Method by Knapp and $r^{-{\theta} }$ Method by Tsutsumi etc., but these methods are all 2-dimentional measuring methods on plane. These simple methods of circular motion accuracy test of NC machine tools have been studied by many reserchers as above, but it is not yet settled in the code of measuring methods of motion errors of NC machine tools, because of errors of measuring units and sensors, and also especially the difficulties of centering of measuring units and the spindle of machining center. In this paper, in use of 2 rotary encoders and 1 magnetic type linear scale with resolution of 0.5 .mu. m, it has become possible for measuring of 3 dimentional space motion accuracy.

• 한국정밀공학회지
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• 제16권2호통권95호
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• pp.201-210
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• 1999

One of the major limitations of productivity and quality in metal cutting is the machining accuracy of machine tools. The machining accuracy is affected by geometric and thermal errors of the machine tools. Therefore, a key requirement for improving te machining accuracy and product quality is to reduce the geometric and thermal errors of machine tools. This study models geometric error for error analysis and develops on-machine measurement system by which the volumetric erors are measured. The geometric error is modeled using form shaping function(FSF) which is defined as the mathematical relationship between form shaping motion of machine tool and machined surface. The constant terms included in the error model are found from the measurement results of on-machine measurement system. The developed on-machine measurement system consists of the spherical ball artifact (SBA), the touch probe unit with a star type stylus, the thermal data logger and the personal computer. Experiments, performed with the developed measurement system, show that the system provides a high measuring accuracy, with repeatability of ${\pm}2{\mu}m$ in X, Y and Z directions.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.838-841
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• 2000

To improve the accuracy of products and improve the product quality, we need to enhance the machining accuracy of the machine tools. To this point of view, measurement and inspection of finished part as well as error analysis of machine tools has been studied for last several decades. OMM(On the Machine Measurement) has been issued to alternate with CMM, pointing out disadvantages of high expenses and lots of setting time in CMM. In this paper, we study 1) the spherical surface manufacturing by volumetric error compensation of machine tool, 2) the system development of OMM without detaching work piece from a bed of machine tool after working. 3) the generation of the finished part profile by On the machine measurement. Furthermore, the output of OMM is compared with that of CMM, and verified the feasibility of the measurement system.

• 한국기계가공학회지
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• 제11권3호
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• pp.174-181
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• 2012

The spindle unit is a core part in high precision machine tool. Rotation accuracy of spindle unit is needed for high dignity cutting and improving the performance of machine tool. However, there are many factors to effect to rotational error motion(rotation accuracy). This study studied how rotational error motion is variation when unbalance amount is variation. Rotation accuracy of initial spindle unit is decided depending on parts and assembly such as bearing. When it is rotation, vibration and noise is appeared depending on volume of unbalance amount, so it works to decrease unbalance amount. The purpose of the study tests that unbalance amount how much effects to initial rotation condition. The result of the study shows that accuracy of parts and assembly is highly necessary to reach high rotation accuracy and unbalance amount hardly effects to initial rotation accuracy. However, it shorten spindle's life because vibration and noise is increasing by increasing unbalance amount and we can expect situation that rotation accuracy is falling by long time operation.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.190-198
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• 2023

To enhance customer satisfaction for higher profits, an e-commerce sector can establish a continuous relationship and acquire new customers. Utilize machine-learning models to analyse their customer's behavioural evidence to produce their competitive advantage to the e-commerce platform by helping to improve overall satisfaction. These models will forecast customers who will churn and churn causes. Forecasts are used to build unique business strategies and services offers. This work is intended to develop a machine-learning model that can accurately forecast retainable customers of the entire e-commerce customer data. Developing predictive models classifying different imbalanced data effectively is a major challenge in collected data and machine learning algorithms. Build a machine learning model for solving class imbalance and forecast customers. The satisfaction accuracy is used for this research as evaluation metrics. This paper aims to enable to evaluate the use of different machine learning models utilized to forecast satisfaction. For this research paper are selected three analytical methods come from various classifications of learning. Classifier Selection, the efficiency of various classifiers like Random Forest, Logistic Regression, SVM, and Gradient Boosting Algorithm. Models have been used for a dataset of 8000 records of e-commerce websites and apps. Results indicate the best accuracy in determining satisfaction class with both gradient-boosting algorithm classifications. The results showed maximum accuracy compared to other algorithms, including Gradient Boosting Algorithm, Support Vector Machine Algorithm, Random Forest Algorithm, and logistic regression Algorithm. The best model developed for this paper to forecast satisfaction customers and accuracy achieve 88 %.